It's good that someon spent time writing this direction of deep learning for the non-data science IT people.
September 23, 2024 by A Reviewer (TW)
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Look inside
A vital guide to building the platforms and systems that bring deep learning models to production.
In Designing Deep Learning Systems you will learn how to:
Deep learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning’s design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You’ll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting—and lucrative—career as a deep learning engineer.
In Designing Deep Learning Systems you will learn how to:
- Transfer your software development skills to deep learning systems
- Recognize and solve common engineering challenges for deep learning systems
- Understand the deep learning development cycle
- Automate training for models in TensorFlow and PyTorch
- Optimize dataset management, training, model serving and hyperparameter tuning
- Pick the right open-source project for your platform
Deep learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning’s design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You’ll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting—and lucrative—career as a deep learning engineer.
about the technology
To be practically usable, a deep learning model must be built into a software platform. As a software engineer, you need a deep understanding of deep learning to create such a system. Th is book gives you that depth.about the book
Designing Deep Learning Systems: A software engineer's guide teaches you everything you need to design and implement a production-ready deep learning platform. First, it presents the big picture of a deep learning system from the developer’s perspective, including its major components and how they are connected. Then, it carefully guides you through the engineering methods you’ll need to build your own maintainable, efficient, and scalable deep learning platforms.what's inside
- The deep learning development cycle
- Automate training in TensorFlow and PyTorch
- Dataset management, model serving, and hyperparameter tuning
- A hands-on deep learning lab
about the reader
For software developers and engineering-minded data scientists. Examples in Java and Python.Written by true industry experts. Their insights are invaluable for software engineers looking to design and implement maintainable platforms for DL model development that meet the highest standards of efficiency and scalability.
Invaluable and timely insights for teams expanding their DL systems. This book anticipates the needs of a diverse set of organizations, and its content can be easily tailored to your current situation or your personal interests.
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March 30, 2023 by Muhammad F. (MY)
“beneficial”
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July 21, 2022 by yuzaihuan (JiangSu, CN)
“help me to know about the DL using in engineering, but would like to know more on how to setup the test environment on my own laptop, so I can test each example step by step.”
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valued buying
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want to use new skill in real project.
March 30, 2022 by A Reviewer (IL)
“Best”
February 27, 2022 by A Reviewer (US)
“We need more books like this!”
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